Arctic sea level variability from high-resolution model simulations and implications for the Arctic observing system

Two high-resolution model simulations are used to investigate the spatiotemporal variability of the Arctic Ocean sea level. The model simulations reveal barotropic sea level variability at periods of < 30 d, which is strongly captured by bottom pressure observations. The seasonal sea level variability is driven by volume exchanges with the Pacific and Atlantic oceans and the redistribution of the water by the wind. Halosteric effects due to river runoff and evaporation minus precipitation ice melting/formation also contribute in the marginal seas and seasonal sea ice extent regions. In the central Arctic Ocean, especially the Canadian Basin, the decadal halosteric effect dominates sea level variability. The study confirms that satellite altimetric observations and Gravity Recovery and Climate Experiment (GRACE) could infer the total freshwater content changes in the Canadian Basin at periods longer than 1 year, but they are unable to depict the seasonal and subseasonal freshwater content changes. The increasing number of profiles seems to capture freshwater content changes since 2007, encouraging further data synthesis work with a more complicated interpolation method. Further, in situ hydrographic observations should be enhanced to reveal the freshwater budget and close the gaps between satellite altimetry and GRACE, especially in the marginal seas.

Indian Ocean Dynamic Sea Level, Variability And Projections In CMIP6 Models

The regional sea level variability and its projection amidst the global sea level rise is one of the major concerns for coastal communities. The dynamic sea level plays a major role in the observed spatial deviations in regional sea level rise from the global mean. The present study evaluates 27 climate model simulations from the sixth phase of the coupled model intercomparison project (CMIP6) for their representation of the historical mean states, variability and future projections for the Indian Ocean. Most models reproduce the observed mean state of the dynamic sea level realistically, however consistent positive bias is evident across the latitudinal range of the Indian Ocean. The strongest sea level bias is seen along the Antarctic Circumpolar Current (ACC) regime owing to the stronger than observed south Indian Ocean westerlies and its equatorward bias. Further, this equatorward shift of the wind field resulted in stronger positive windstress curl across the southeasterly trade winds in the southern tropical basin and easterly wind bias along the equatorial waveguide. These anomalous easterly equatorial winds cause upwelling in the eastern part of the basin and keeps the thermocline shallower in the model than observed, resulted in enhanced variability for the dipole zonal mode or Indian Ocean dipole in the tropics. In the north Indian Ocean, the summer monsoon winds are weak in the model causing weaker upwelling and positive sea level bias along the western Arabian Sea. The high-resolution models compare better in simulating the sea level variability, particularly in the eddy dominated regions like the ACC regime in interannual timescale. However, these improved variabilities do not necessarily produce a better mean state likely due to the enhanced mixing driven by parametrizations set in these high-resolution models. Finally, the overall pattern of the projected dynamic sea level rise is found to be similar for the mid (SSP2-4.5) and high-end (SSP5-8.5) scenarios, except that the magnitude is higher under the high emission situation. Notably, the projected dynamic sea level change is found to be milder when only the best performing models are used compared to the full ensemble.

Atlantic coastal sea level variability and synoptic-scale meteorological forcing

Anomalous sea levels along the Mid- and South- Atlantic coasts of the United States are often linked to atmosphere- ocean dynamics, remote- and local- scale forcing and other factors linked to cyclone passage, winds, waves, and storm surge. Herein, we examine sea level variability along the U.S. Atlantic coast through satellite altimeter and coastal tide gauge data within the context of synoptic-scale weather pattern forcing. Altimetry, derived from sea level anomaly (SLA) data between 1993 and 2019 were compared with Self Organizing Map (SOM)-based atmospheric circulation and surface wind field categorizations to reveal spatiotemporal patterns and their inter-relationships with high water-level conditions at tide gauges. Regional elevated sea level patterns and variability were strongly associated with synergistic patterns of atmospheric circulation and wind. Recurring atmospheric patterns associated with high-tide flooding events and flood risk were identified, as were specific regional oceanographic variability patterns of SLA response. The incorporation of combined metrics of wind and circulation patterns further isolate atmospheric drivers of high tide flood events and may have particular significance for predicting future flood events over multiple spatial and temporal scales.

Decadal sea-level variability in the Australasian Mediterranean Sea

Strong regional sea-level trends, mainly related to basin-wide wind stress anomalies, have been observed in the western tropical Pacific over the last 3 decades. Analyses of regional sea level in the densely populated regions of the neighbouring Australasian Mediterranean Sea (AMS; also called tropical Asian seas) are hindered by its complex topography and respective studies are sparse. We used a series of global eddy-permitting ocean models, including a high-resolution configuration that resolves the AMS with 120∘ horizontal resolution, forced by a comprehensive atmospheric forcing product over 1958–2016 to characterize the patterns and magnitude of decadal sea-level variability in the AMS. The nature of this variability is elucidated further by sensitivity experiments with interannual variability restricted to either the momentum or buoyancy fluxes, building on an experiment employing a repeated-year forcing without interannual variability in all forcing components. Our results suggest that decadal fluctuations of the El Niño–Southern Oscillation (ENSO) account for over 80 % of the variability in all deep basins of the region, except for the central South China Sea (SCS). Changes related to the Pacific Decadal Oscillation (PDO) are most pronounced in the shallow Arafura and Timor seas and in the central SCS. On average, buoyancy fluxes account for less than 10 % of decadal SSH variability, but this ratio is highly variable over time and can reach values of up to 50 %. In particular, our results suggest that buoyancy flux forcing amplifies the dominant wind-stress-driven anomalies related to ENSO cycles. Intrinsic variability is mostly negligible except in the SCS, where it accounts for 25 % of the total decadal SSH variability.

Atmospherically forced sea-level variability in western Hudson Bay, Canada

In recent years, significant trends toward earlier breakup and later freeze-up of sea ice in Hudson Bay have led to a considerable increase in shipping activity through the Port of Churchill, which is located in western Hudson Bay and is the only deep-water ocean port in the province of Manitoba. Therefore, understanding sea-level variability at the port is an urgent issue crucial for safe navigation and coastal infrastructure. Using tidal gauge data from the port along with an atmospheric reanalysis and Churchill River discharge, we assess environmental factors impacting synoptic to seasonal variability of sea level at Churchill. An atmospheric vorticity index used to describe the wind forcing was found to correlate with sea level at Churchill. Statistical analyses show that, in contrast to earlier studies, local discharge from the Churchill River can only explain up to 5 % of the sea-level variability. The cyclonic wind forcing contributes from 22 % during the ice-covered winter–spring season to 30 % during the ice-free summer–fall season due to cyclone-induced storm surges generated along the coast. Multiple regression analysis revealed that wind forcing and local river discharge combined can explain up to 32 % of the sea-level variability at Churchill. Our analysis further revealed that the seasonal cycle of sea level at Churchill appears to be impacted by the seasonal cycle in atmospheric circulation rather than by the seasonal cycle in local discharge from the Churchill River, particularly post-construction of the Churchill River diversion in 1977. Sea level at Churchill shows positive anomalies for September–November compared to June–August. This seasonal difference was also revealed for the entire Hudson Bay coast using satellite-derived sea-level altimetry. This anomaly was associated with enhanced cyclonic atmospheric circulation during fall, reaching a maximum in November, which forced storm surges along the coast. Complete sea-ice cover during winter impedes momentum transfer from wind stress to the water column, reducing the impact of wind forcing on sea-level variability. Expanding our observations to the bay-wide scale, we confirmed the process of wind-driven sea-level variability with (i) tidal-gauge data from eastern Hudson Bay and (ii) satellite altimetry measurements. Ultimately, we find that cyclonic winds generate sea-level rise along the western and eastern coasts of Hudson Bay at the synoptic and seasonal timescales, suggesting an amplification of the bay-wide cyclonic geostrophic circulation in fall (October–November), when cyclonic vorticity is enhanced, and Hudson Bay is ice-free.

Atmospheric and Climatic Drivers of Tide Gauge Sea Level Variability along the East and South Coast of South Africa

Atmospheric forcing and climate modes of variability on various timescales are important drivers of sea level variability. However, the influence of such drivers on sea level variability along the South African east and south coast has not yet been adequately investigated. Here, we determine the timescales of sea level variability and their relationships with various drivers. Empirical Mode Decomposition (EMD) was applied to seven tide gauge records and potential forcing data for this purpose. The oscillatory modes identified by the EMD were summed to obtain physically more meaningful timescales—specifically, the sub-annual (less than 18 months) and interannual (greater than two years) scales. On the sub-annual scale, sea level responds to regional zonal and meridional winds associated with mesoscale and synoptic weather disturbances. Ekman dynamics resulting from variability in sea level pressure and alongshore winds are important for the coastal sea level on this timescale. On interannual timescales, there were connections with ENSO, the Indian Ocean Dipole (IOD) and the Southern Annular Mode (SAM), although the results are not consistent across all the tide gauge stations and are not particularly strong. In general, El Niño and positive IOD events are coincident with high coastal sea levels and vice versa, whereas there appears to be an inverse relationship between SAM phase and sea level.